Hadoop MapReduce总排序字数

Question

我想在mapreduce计数中做一个完整的排序。

public int run(String[] args) throws Exception {
  Job job = Job.getInstance(getConf(), "wordcount");
  job.setJarByClass(this.getClass());
  FileInputFormat.addInputPath(job, new Path(args[0]));
  FileOutputFormat.setOutputPath(job, new Path(args[1]));
  job.setMapperClass(Map.class);

  //Total Sort
  job.setPartitionerClass(TotalOrderPartitioner.class);
  InputSampler.Sampler<Text, IntWritable> sampler = new InputSampler.RandomSampler<Text, IntWritable>(0.1, 10000, 10);
  InputSampler.writePartitionFile(job, sampler);
  Path inputDir = new Path(args[2] + "/_tmp");
  Path partitionFile = new Path(inputDir, "_partitioning");
  TotalOrderPartitioner.setPartitionFile(job.getConfiguration(),partitionFile);
  InputSampler.writePartitionFile(job, sampler);

  job.setReducerClass(Reduce.class);
  job.setOutputKeyClass(Text.class);
  job.setOutputValueClass(IntWritable.class);  

  return job.waitForCompletion(true) ? 0 : 1;
}

但我遇到了像java.io.IOException: wrong key class: org.apache.hadoop.io.Text is not class org.apache.hadoop.io.LongWritable这样的错误

我不明白InputSampler.RandomSampler是如何工作的。

Answer 1

在上面的代码中，没有为作业设置InputFormat，因此将采用默认设置，即TextInputFormat<LongWritable,Text>。

对于InputSampler.RandomSampler<Text, IntWritable>，它被配置为Text，IntWritable，它与TextInputFormat不匹配。

由于InputFormat和InputSampler之间存在类型不匹配，因此会引发错误。